Error Rate Calculation Research Articles

Efficient Modeling of Single Event Transient Effect with Limited Peak Current: Implications for Logic Circuits.

The problem that the conventional double-exponential transient current model (DE model) can overdrive the circuit, which leads to the overestimation of the soft error rate of the logic cell, is solved. Our work uses a new and accurate model for predicting the soft error rate that brings the soft error rate closer to the actual. The piecewise double-exponential transient current model (PDE model) is chosen, and the accuracy of the model is reflected using the Layout Awareness Single Event Multi Transients Soft Error Rate Calculation tool (LA-SEMT-SER tool). The model can characterize transient current pulses piecewise and limit the peak current magnitude to not exceed the conduction current. TCAD models are constructed from 28 nm process library and cell layouts. The transfer characteristic curves of devices are calibrated, and functional timing verification is performed to ensure the accuracy of the TCAD model. The experimental results show that the PDE model is not only more consistent with TCAD simulation than the DE model in modeling the single event transient currents of the device, but also that the SER calculated by the LA-SEMT-SER tool based on the PDE model has a smaller error than the SER calculated by the LA-SEMT-SER tool based on the DE model.

Being confident in confidence scores: calibration in deep learning models for camera trap image sequences

AbstractIn ecological studies, machine learning models are increasingly being used for the automatic processing of camera trap images. Although this automation facilitates and accelerates the identification step, the results of these models may lack interpretability and their immediate applicability to ecological downstream tasks (e.g. occupancy estimation) remains questionable. In particular, little is known about their calibration, a property that allows confidence scores to be interpreted as probabilities that model's predictions are true. Using a large and diverse European camera trap dataset, we investigate whether deep learning models for species classification in camera trap images are well calibrated. Additionally, as camera traps are often configured to take multiple photos of the same event, we also explore the calibration of predictions aggregated across sequences of images. Finally, we study the effect and the practicality of a post‐hoc calibration method, i.e. temperature scaling, for predictions made at image and sequence levels. Based on five established models and three independent test sets, we show that averaging the logits over the sequence, selecting an appropriate architecture, and optionally using temperature scaling can produce well‐calibrated models. Our findings have clear implication for, for instance, the calculation of error rates or the selection of confidence score thresholds in ecological studies making use of artificial intelligence models.

Enhanced repetition codes for the cross-platform comparison of progress towards fault-tolerance

Achieving fault-tolerance will require a strong relationship between the hardware and the protocols used. Different approaches will therefore naturally have tailored proof-of-principle experiments to benchmark progress. Nevertheless, repetition codes have become a commonly used basis of experiments that allow cross-platform comparisons. Here we propose methods by which repetition code experiments can be expanded and improved, while retaining cross-platform compatibility. We also consider novel methods of analyzing the results, which offer more detailed insights than simple calculation of the logical error rate.

A systematic approach to manual calibration and validation of building energy simulation

PurposeThis study aims to create an efficient approach to validate building energy simulation models amidst challenges from time-intensive data collection. Emphasizing precision in model calibration through strategic short-term data acquisition, the systematic framework targets critical adjustments using a strategically captured dataset. Leveraging metrics like Mean Bias Error (MBE) and Coefficient of Variation of Root Mean Square Error (CV(RMSE)), this methodology aims to heighten energy efficiency assessment accuracy without lengthy data collection periods.Design/methodology/approachA standalone school and a campus facility were selected as case studies. Field investigations enabled precise energy modeling, emphasizing user-dependent parameters and compliance with standards. Simulation outputs were compared to short-term actual measurements, utilizing MBE and CV(RMSE) metrics, focusing on internal temperature and CO2 levels. Energy bills and consumption data were scrutinized to verify natural gas and electricity usage against uncertain parameters.FindingsDiscrepancies between initial simulations and measurements were observed. Following adjustments, the standalone school 1’s average internal temperature increased from 19.5 °C to 21.3 °C, with MBE and CV(RMSE) aiding validation. Campus facilities exhibited complex variations, addressed by accounting for CO2 levels and occupancy patterns, with similar metrics aiding validation. Revisions in lighting and electrical equipment schedules improved electricity consumption predictions. Verification of natural gas usage and monthly error rate calculations refined the simulation model.Originality/valueThis paper tackles Building Energy Simulation validation challenges due to data scarcity and time constraints. It proposes a strategic, short-term data collection method. It uses MBE and CV(RMSE) metrics for a comprehensive evaluation to ensure reliable energy efficiency predictions without extensive data collection.

Vehicle Speed Detection using Haar Cascade Classifier and Correlation Tracking

Objectives: The aim of this study is to develop an efficient and cost-effective solution for predicting vehicle speeds using recorded video data. Methods: The proposed system employs a combination of image processing techniques and computer vision to calibrate cameras for traffic simulation, enabling the extraction of information on average vehicle speeds. It utilizes the Haar Cascade Classifier for object detection, followed by a correlation tracker for vehicle tracking. Speed estimation is achieved through the frame differencing method. The dataset comprises 90 minutes of recorded data from highway cameras, showcasing diverse traffic scenarios with various vehicle types (trucks, trailers, cars, buses, and bikes) at varying speeds. Predicted values are compared with ground truth data obtained from a GPS-equipped car, using Mean Absolute Error (MAE) as the evaluation metric. Findings: The algorithm's performance is evaluated, resulting in an average error rate of 1.72 km/h (2.07%). These findings are compared with state-of-the-art data. Novelty: This study introduces a novel system that combines the Haar Cascade Classifier, correlation tracker, and frame differencing method to track vehicle positions, incorporating bike detection into the analysis, and calculate their moving speeds. A relative analysis underscores the system's performance, emphasizing its effectiveness in real-world applications and demonstrating refinement in accuracy assessment. Keywords: Image processing, Vehicle speed estimation, Haar Cascade Classifier, Correlation tracker, Error rate calculation, Computer vision

Wheat Quantity Monitoring Methods Based on Inventory Measurement and SVR Prediction Model

Due to the influences of the storage environment, water content change, particle settlement, natural loss, and other factors, the distribution density of wheat and the volume of grain pile in the storage process are gradually changed so that the single weight calculation method cannot objectively evaluate the storage quantity of wheat and also causes difficulties to the regular inspection of the quantity of wheat stock. To meet the practical needs of wheat inventory monitoring, a wheat inventory monitoring method based on inventory measurement and the support vector machine regression (SVR) prediction model is proposed. By collecting the working papers for the physical inspection of wheat in grain warehouses in Shanxi province, Hebei province, Henan province, Jiangsu province, and other places, the storage time, storage weight, storage moisture content, measured moisture content, measured volume weight, measured net volume, and measured weight for inspection were selected as training samples for the SVR prediction model, and kernel function selection and parameter optimization were carried out. We developed an optimal prediction model for the amount of wheat in the grain depots. In the actual grain store measurement process, the net volume of wheat in the current grain store was obtained by a laser volumetric measuring apparatus, the actual bulk density of wheat was sampled, and the actual moisture content of wheat was measured by sampling. The three samples, their storage time, their storage moisture content, and their storage weight were fed into the trained SVR prediction model as new samples, and the predicted weight of the wheat in the current grain store was obtained from the output. The error rate calculation procedure was introduced to achieve an anomalous judgment error rate for grain depots. The experimental results showed that the SVR prediction model based on the linear kernel function had a very low mean squared error and high determination coefficient, and the average prediction accuracy of the grain stock error rate reached 93.2 percent, which can meet the requirements of wheat quantity monitoring in grain warehouses.

New insights into diffusion–collection modeling of radiation-induced charge in semiconductor devices

Charge diffusion from an ion track and its collection by a biased contact in a semiconductor domain is modeled and analyzed within the framework of the so-called diffusion–collection approach. We successively examine the case of charge diffusion from a point source and from a linear distribution, introducing and discussing the concept of collection velocity at the point where the collection current is evaluated. Analytical formulations of the collected charge, collection current, and collection velocity are developed. Implications for the calculation of the soft error rate in complementary metal-oxide-semiconductor circuits exposed to ionizing particles are derived. Finally, our model provides new insights into the correct definition of the charge collection velocity in collection–diffusion models.

Closed-Form Analysis of the α-Beaulieu-Xie Shadowed Fading Channel

The presented research proposes the α-modification of the Beaulieu-Xie shadowed fading channel for wireless communications. For the assumed model the closed-form analytical description of the basic statistical characteristics is carried out (i.e., probability density function, cumulative distribution function, and their asymptotics). The derived statistical description is exemplified on the problems of the average bit error rate and ergodic capacity calculation, for which the exact analytic and high signal-to-noise ratio asymptotic expressions are derived. The performed extensive numerical analysis demonstrates high correspondence with the analytical work and helps to study the dependence of the channel nonlinearity effects on the bit error probability.

Advanced and Easy Expression of Bit Error Rate Calculation for Multiple DF Relay using Rayleigh Fading Channel

Advanced and Easy Expression of Bit Error Rate Calculation for Multiple DF Relay using Rayleigh Fading Channel

Gaussian-Distributed Spread-Spectrum for Covert Communications.

Covert communication techniques play a crucial role in military and commercial applications to maintain the privacy and security of wireless transmissions from prying eyes. These techniques ensure that adversaries cannot detect or exploit the existence of such transmissions. Covert communications, also known as low probability of detection (LPD) communication, are instrumental in preventing attacks such as eavesdropping, jamming, or interference that could compromise the confidentiality, integrity, and availability of wireless communication. Direct-sequence spread-spectrum (DSSS) is a widely used covert communication scheme that expands the bandwidth to mitigate interference and hostile detection effects, reducing the signal power spectral density (PSD) to a low level. However, DSSS signals possess cyclostationary random properties that an adversary can exploit using cyclic spectral analysis to extract useful features from the transmitted signal. These features can then be used to detect and analyse the signal, making it more susceptible to electronic attacks such as jamming. To overcome this problem, a method to randomise the transmitted signal and reduce its cyclic features is proposed in this paper. This method produces a signal with a probability density function (PDF) similar to thermal noise, which masks the signal constellation to appear as thermal white noise to unintended receivers. This proposed scheme, called Gaussian distributed spread-spectrum (GDSS), is designed such that the receiver does not need to know any information about the thermal white noise used to mask the transmit signal to recover the message. The paper presents the details of the proposed scheme and investigates its performance in comparison to the standard DSSS system. This study used three detectors, namely, a high-order moments based detector, a modulation stripping detector, and a spectral correlation detector, to evaluate the detectability of the proposed scheme. The detectors were applied to noisy signals, and the results revealed that the moment-based detector failed to detect the GDSS signal with a spreading factor, N = 256 at all signal-to-noise ratios (SNRs), whereas it could detect the DSSS signals up to an SNR of -12 dB. The results obtained using the modulation stripping detector showed no significant phase distribution convergence for the GDSS signals, similar to the noise-only case, whereas the DSSS signals generated a phase distribution with a distinct shape, indicating the presence of a valid signal. Additionally, the spectral correlation detector applied to the GDSS signal at an SNR of -12 dB showed no identifiable peaks on the spectrum, providing further evidence of the effectiveness of the GDSS scheme and making it a favourable choice for covert communication applications. A semi-analytical calculation of the bit error rate is also presented for the uncoded system. The investigation results show that the GDSS scheme can generate a noise-like signal with reduced identifiable features, making it a superior solution for covert communication. However, achieving this comes at a cost of approximately 2 dB on the signal-to-noise ratio.

Abstract 529: SNAQ-SEQ™: Use of synthetic internal standards in conjunction with poisson exact test to call variants in contrived circulating tumor DNA specimens

Abstract Background: Targeted next generation sequencing (NGS) analysis of circulating tumor (ct) DNA promises to significantly advance targeted therapy and potentially early diagnosis of cancer. However, targeted NGS has poor accuracy for calling known variants with VAF below 0.5%. The goal of this study from the FDA-Sequencing and Quality Control Phase 2 (SEQC2) consortium was to develop and validate bioinformatic and biostatistical methods that enable incorporation of synthetic competitive internal standards (IS) in targeted NGS analysis of actionable tumor mutations. Methods: A synthetic IS spike-in was designed for each actionable mutation target, suitable for use in NGS following targeted PCR or hybrid-capture enrichment and either with unique molecular index (UMI) or non-UMI library preparation. Contrived ctDNA reference samples developed by the SEQC2 consortium containing actionable mutations at known variant allele fraction were used. An aliquot of each sample was mixed with a mixture of IS. Following Illumina TST170 enrichment and library preparation, each library was sequenced, then native template (NT) sequences were separated from IS sequences bioinformatically. In SNAQ-SEQ™ analysis, Poisson Exact Test (PET) analysis was used to calculate the statistical difference between each sample library NT variant VAF and respective IS variant VAF. Analysis was based on NT variant count and position coverage (i.e., copies recovered in library preparation) and IS count and position coverage. PET performed an exact test of a simple null hypothesis about the ratio between two rate parameters in Poisson distribution. Results: Stochastic sampling effect on IS error detection was minimized by ensuring an IS/NT ratio of 2.5 or greater. Under the specified conditions, in which a minimum of two NT variant observations were required for a call, the IS was able to estimate NGS background error for each sample when a minimum IS:NT ratio of 2.5:1 was used. Without use of IS information, the Illumina pipeline called 73% (41/56) of known TP variants in the 0.1% - 0.3% VAF range. In contrast, SNAQ-SEQ™ analysis (PET analysis of IS and NT information) increased TP detection sensitivity to 86% (48/56), for a 13% increase in sensitivity, with no false positives. Conclusion: Following mixture of contrived ctDNA reference samples with IS, PET analysis enabled calculation of technical error rate, limit of blank, and limit of detection for each variant at each nucleotide position, in each sample. Using this SNAQ-SEQ™ analysis, true positive mutations with variant allele fraction too low for detection by current practice were detected with this method, thereby increasing sensitivity. SNAQ-SEQ™ provides QC that is already standard operating procedure in clinical laboratories for analysis by high pressure liquid chromatography and mass spectrometry. Citation Format: James C. Willey, Erin Crawford, Daniel J. Craig, Joshua Xu, Nathan Haseley, Jennifer Lococo, Tom Morrison. SNAQ-SEQ™: Use of synthetic internal standards in conjunction with poisson exact test to call variants in contrived circulating tumor DNA specimens [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 529.

기계번역의 특허 전문용어 한영번역에서 나타나는 오류 양상 분석 – 구글 번역 결과를 중심으로

Terminology translation plays a key role in technical machine translation. This paper conducts quantitative and qualitative evaluation and presents a comprehensive error analysis on terminology translation from Korean to English. For this study, 637 terms are selected from a patent domain corpus. Among them, 425 terms are translated correctly while other 212 terms have one or more errors. Those identified errors are classified into seven error categories which include addition, omission, lexical errors, order errors, morphological errors, partial errors, and miscellanies. Among them, partial errors and morphological errors are the two top error categories, and lexical errors and omission cases are also high. The study also presents n-gram wise error rates. The calculation of n-gram wise terminology translation error rates shows that the curve for the Google Translation results goes upwards with the increasing size of n. This shows that neural machine translation can be vulnerable in translating a higher-order of n-gram terms. This study has implications for Korean-English machine translation research, in that it classifies error cases spotted in machine translation of terminology which is critical in securing accuracy of translations.

Quantum error correction with higher Gottesman-Kitaev-Preskill codes: Minimal measurements and linear optics

We propose two schemes to obtain Gottesman-Kitaev-Preskill (GKP) error syndromes by means of linear optical operations, homodyne measurements and GKP ancillae. This includes showing that for a concatenation of GKP codes with a $[n,k,d]$ stabilizer code only $2n$ measurements are needed in order to obtain the complete syndrome information, significantly reducing the number of measurements in comparison to the canonical concatenated measurement scheme and at the same time generalizing linear-optics-based syndrome detections to higher GKP codes. Furthermore, we analyze the possibility of building the required ancilla states from single-mode states and linear optics. We find that for simple GKP codes this is possible, whereas for concatenations with qubit Calderbank-Shor-Steane (CSS) codes of distance $d\geq3$ it is not. We also consider the canonical concatenated syndrome measurements and propose methods for avoiding crosstalk between ancillae. In addition, we make use of the observation that the concatenation of a GKP code with a stabilizer code forms a lattice in order to see the analog information decoding of such codes from a different perspective allowing for semi-analytic calculations of the logical error rates.

The novel approach to the closed-form average bit error rate calculation for the Nakagami-m fading channel

The research presents a procedure of the closed-form average bit error rate evaluation for wireless communication systems in the presence of multipath fading. A generalization of the classical moment generating function is applied, and a connection between the Hankel-type contour-integral representation of the Marcum Q-function and Gauss Q-function is obtained and applied to the analytic derivation of the quadrature amplitude modulated signal average bit error rate in the presence of Nakagami-m fading. The correctness of the obtained solution was verified, and its computational efficiency (in terms of accuracy and time gain), compared with the prevailing approximation, was demonstrated. The proposed methodology can be extended to a wide variety of composite channels.

Comparison of GATK and DeepVariant by trio sequencing

While next-generation sequencing (NGS) has transformed genetic testing, it generates large quantities of noisy data that require a significant amount of bioinformatics to generate useful interpretation. The accuracy of variant calling is therefore critical. Although GATK HaplotypeCaller is a widely used tool for this purpose, newer methods such as DeepVariant have shown higher accuracy in assessments of gold-standard samples for whole-genome sequencing (WGS) and whole-exome sequencing (WES), but a side-by-side comparison on clinical samples has not been performed. Trio WES was used to compare GATK (4.1.2.0) HaplotypeCaller and DeepVariant (v0.8.0). The performance of the two pipelines was evaluated according to the Mendelian error rate, transition-to-transversion (Ti/Tv) ratio, concordance rate, and pathological variant detection rate. Data from 80 trios were analyzed. The Mendelian error rate of the 77 biological trios calculated from the data by DeepVariant (3.09 ± 0.83%) was lower than that calculated from the data by GATK (5.25 ± 0.91%) (p < 0.001). DeepVariant also yielded a higher Ti/Tv ratio (2.38 ± 0.02) than GATK (2.04 ± 0.07) (p < 0.001), suggesting that DeepVariant proportionally called more true positives. The concordance rate between the 2 pipelines was 88.73%. Sixty-three disease-causing variants were detected in the 80 trios. Among them, DeepVariant detected 62 variants, and GATK detected 61 variants. The one variant called by DeepVariant but not GATK HaplotypeCaller might have been missed by GATK HaplotypeCaller due to low coverage. OTC exon 2 (139 bp) deletion was not detected by either method. Mendelian error rate calculation is an effective way to evaluate variant callers. By this method, DeepVariant outperformed GATK, while the two pipelines performed equally in other parameters.

Fast Feed-Forward Optical and Electrical Gain Control to Extend the Dynamic Range of the Burst-Mode Digital Coherent Receiver for High-Speed TDM-PON Systems

This paper introduces a new burst-mode coherent receiver configuration that drastically widens the receiver input dynamic range. Its key advance is a fast feed forward gain control scheme for both a semiconductor optical amplifier (SOA) used as a preamplifier and trans-impedance amplifiers (TIAs) set at the coherent receiver. The two-stage optical and electrical gain control greatly decreases the received burst signal's power variations and increases the receiver dynamic range which attenuates the quantization errors in analogue-to-digital conversion (ADC). To elucidate the receiver sensitivity characteristics, bit error rate (BER) calculations are conducted on 10 Gbit/s single polarization quadrature phase shift keying (SP-QPSK) signal coherent reception. The calculations focus on two significant parameters that greatly impact the quantization noise; ADC vertical resolution and received signal's state of polarization (SOP). The calculation results confirm that the proposed configuration achieves high sensitivity, better than −44 dBm, and wide dynamic range of 30 dB in the worst SOP condition, even when 5-bit ADC is used. Transmission experiments verify the calculated sensitivities and extremely high loss budget of 48.6 dB is achieved in 40-km single mode fiber (SMF) transmission. These results show that the proposal has the potential to realize 10 Gbit/s class long-reach and high splitting ratio PONs; the extremely wide dynamic range yields 40 km reach PON systems with 512- or 1024-way splits with no change in receiver configuration.

Evaluation of High-Speed Link Parameters for Highly Reliable Reconfigurable Systems Based on S-Parameters and BER

Purpose of research. is to improve signal transmission parameters in high-speed signal transmission lines, including between programmable logic integrated circuits (PLIC). This improvement in signal transmission parameters is necessary to increase throughput of modern highly reliable reconfigurable systems to ensure data transfer rate of up to tens of Gbit/s. It can be done considering the influence of electrical and structural parameters of multi-layer printed circuit boards (MPCB) on them. It is possible to provide such high data rates by using a wider frequency band of transmitted signals. One of the existing approaches to this problem is to increase "physical" frequency of transmitted information signals to 25-300 GHz, which is sufficient to achieve desired rates.Methods. A method for estimating quality of high-speed signal transmission lines based on the definition of standardized methods for analyzing signal transmission parameters, such as JCOM, S-parameters and BER is proposed in the article. This method allows evaluating high-speed communication lines. Thus, the Channel Operating Margin (COM)/JCOM parameter can be used to estimate the quality of a digital communication channel - a standardized method for determining the overall channel quality indicator. Known methods are used to estimate such signal transmission parameters as S11 reflection coefficient and S21 attenuation coefficient (S-Parameters). These methods are used to estimate attenuation and loss of the information signal in the path, when copies of the signal reflected from inhomogeneities affect the original and lead to its distortion. Simulation of such parameter as Bit Error Rate (BER) is carried out according to G.821/G.826/M2100 rationing and quality control methodology.Results. The main metrics were selected to evaluate the quality of high-speed signal transmission lines. It is based on the evaluation of such signal transmission parameters as Channel Operating Margin (COM), S-parameters and Bit Error Rate (BER). Numerical evaluations of signal transmission parameters were obtained and their effect on the design parameters of high-speed signal transmission lines was estimated. It is recommended to use at least 1 transition hole between screening polygons in GND separation layers every 0.5 cm or 0.25 cm2 of WFP area. It is for a data rate of less than 25 Gbit/s, It is recommended to use at least 2 transition holes between screening polygons in GND separation layers every 0.5 cm or 0.25 cm² of PV area, if high-speed signal transmission line passes at a distance of closer than 2.5 cm from the power supply circuits in a projection on the layer where the power supply circuits are located.Conclusion. A method for calculating signal transmission parameters on high-speed signaling lines based on the calculation of Channel Operating Margin (COM), S-parameters and Bit Error Rate (BER) parameters is introduced. As part of introduced method, an analysis of signal transmission parameters was carried out. This analysis shows that when the "reference" values of electrical parameters of the line are met, the transfer holes contribute most to the signal distortion; then the layers in which the signal line is located, the number of screening polygons between the signal layers and the layers; in which the power supply circuits, the design parameters of the transition holes, as well as the length and number of segments of the high-speed line pass. Numerical evaluations of minimum number of transition holes and their diameter, the length of segments of differential pairs are given. These results can be used in pre-layout analysis step of high-speed signal transmission lines for computational modules of highly reliable reconfigurable systems.

Performance of Non-Line of Sight Underwater Optical Wireless Communication Links with Spatial Diversity

Line-of-sight (LOS) underwater optical wireless communication (UOWC) transmission may suffer blocking and are not always possible due to obstructions from sea creatures, bubbles, large suspended particles and features of the seabed, especially in coastal and turbid water environments. Thus, we present the performance of a spatially diverse non-line-of-sight (NLOS) UOWC system employing continuous phase modulation (CPM), which is shown to offer sensitivity benefits of several dBs over on–off keying (OOK) without coherent reception. We obtain the channel impulse response (CIR) by using Monte Carlo simulation, including absorption and multiple scattering. Turbulence is included by conditioning the CIR on log-normal statistics. To mitigate the resultant fading, we exploit spatial diversity with equal gain combining at the receiver side. Photon counting at the receiver is employed to accommodate shot noise. We compare the saddlepoint and Gaussian approximations for bit error rate (BER) calculations, using the latter for later calculations as it delivers excellent results and is simpler. Our results show that spatial diversity offers performance improvements, for example an 8 dB sensitivity gain at 10^-9 BER using 1 Gbps 3×1 multiple-input single-output (MISO) transmission over a 20 m link with 0.16 log-amplitude variance. We determine using an upper bound that Intersymbol Interference (ISI) has a significant impact at high bit rates, producing error floors for multiple-output arrangements.

Synergistic Effect of BTI and Process Variations on the Soft Error Rate Estimation in Digital Circuits

Soft errors, aging effects and process variations have become the three most critical reliabil-ity issues for nanoscale complementary metal oxide semiconductor (CMOS) circuits. In this paper, the effects of bias temperature instability (BTI) and process variations on the threshold voltage of MOS devices are theoretically deduced, and the drift of the threshold voltage under the synergistic effect of BTI and process variations is analyzed. Based on the deduced threshold voltage drift formula under the synergistic effect, the critical charge and delay of different logic gates under different aging times in NanGate&#x2019;s 45 nm process are simulated and analyzed. A method based on the change in the critical charge and delay of the soft error rate (SER) calculation considering BTI effect and process variations is given, and the effective-ness of our method comprehensively demonstrated using the ISCAS85,89 benchmarks. As a result, we can observe that the effect of only considering the BTI effect on the critical charge of the circuit is smaller than that of considering both the BTI effect and process variations. The simulation results show that with in-creasing aging time, the synergistic effect of BTI and process variations makes the increase in the soft error rate more serious than the impact of either effect alone.

Efficient Bit Loading Algorithm for OFDM-NOMA Systems With BER Constraints

This paper proposes a novel bit loading algorithm to multicarrier non-orthogonal multiple access (NOMA) systems to maximize the system total throughput while satisfying the users&#x2019; individual quality of service (QoS) constraints. Although bit loading is generally a non-deterministic polynomial-time (NP)-hard problem, even for orthogonal multiple access (OMA), the mutual interference between the users, and the dependence of power coefficients and modulation orders are additional challenges that add substantial complexity to the optimization problem. Therefore, in this paper, we propose an efficient bit loading algorithm for multicarrier NOMA systems and compare the complexity and throughput with a corresponding OMA system. The obtained results show that for the case of NOMA, bit loading provides an additional degree of freedom that allows non-uniform spectrum sharing among the users. In particular scenarios, the system may experience hybrid modes of operation, where the system switches between NOMA and OMA. The obtained numerical results show that NOMA can outperform OMA by 100&#x0025; in terms of spectral efficiency, for a two-user scenario. The complexity of the loading process for NOMA is noticeably higher than OMA, which is due to the high complexity associated with the bit error rate (BER) computation in the case of NOMA.